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Double Supertrend Strategy Backtest (8500+ Trades on 28 Pairs)
Hi everyone, so a few months ago I discovered this post by u/AHoomanBeanz which is a strategy I've never heard of before. Basically, you have 2 Supertrends, a short-term one, and a long-term one and when both Supertrends go in the same direction you take a trade. I took the liberty of modifying the strategy by setting fixed TPs instead of trailing SL with the short-term Supertrend. Check out his post for more info about entries, SL, etc. In order to determine what way is the most efficient, I backtested this exact strategy on all 28 Majors and Minors and took five different approaches to TPs and moving of SL: - 1:1 RRR, No Breakeven SL - 1:1.5 RRR, No BE SL - 1:2 RRR, No BE SL - 1:1.5 RRR, Move SL to BE at 1:1 RRR - 1:2 RRR, Move SL to BE at 1:1RRR There would be many other ways to handle the TPs and SLs but it already took me months to backtest this but if anyone wants to extend this backtest, feel free. The Results Using all 5 ways there were 8 out of 28 pairs that weren't profitable at all. (EURGBP, EURCAD, GBPAUD, GBPNZD, AUDCHF, NZDJPY, CADCHF, CHFJPY) The remaining 20 pairs were profitable with at least one of the 5 ways. So I combined all 20 pairs and their most profitable TP/SL management methods and it turns out that the strategy isn't even that bad considering that you really just have to understand how Supertrends work. Now here are some quick stats: Backtest Period: Jan 2017 - Aug 2020 - Risk Per Trade: 1% - Winrate: 44.66% - Profit Factor: 1.65 - Average Monthly Return: 5.81% - Max Drawdown: 18.4% Notice that the drawdown is pretty high so if you're trading with a prop firm like FTMO you could just risk half as much (0.5% per trade) and your max DD would be 9.2%. Keep in mind that the return would also get cut in half. If you want to get a more detailed view, here's the backtesting spreadsheet (Before anyone asks: I spent 2-4h per day for around 6 weeks backtesting and tracking this stuff.)
This thread is the direct continuation of my previous entry, which you can find here. I have the feeling my rambles may be long, so I'm not going to repeat anything I already said in my previous post for the sake of keeping this brief. What is this? I am backtesting the strategy shared by ParallaxFx. I have just completed my second run of testing, and I am here to share my results with those who are interested. If you want to read more about the strategy, go to my previous thread where I linked it. What changed? Instead of using a fixed target of the -100.0 Fibonacci extension, I tracked both the -61.8 and the -100.0 targets. ParallaxFx used the -61.8 as a target, but never tried the second one, so I wanted to compare the two and see what happens. Where can I see your backtested result? I am going to do something I hope I won't regret and share the link to my spreadsheet. Hopefully I won't be doxxed, but I think I should be fine. You can find my spreadsheet at this link. There are a lot of entries, so it may take a while for them to load. In the "Trades" tab, you will find every trade I backtested with an attached screenshot and the results it would have had with the extended and the unextended target. You can see the UNCOMPOUNDED equity curve in the Summary tab, together with the overall statistics for the system. What was the sample size? I backtested on the Daily chart, from January 2017 to December 2019, over 28 currency pairs. I took a total of 310 trades - although keep in mind that every position is most often composed by two entries, meaning that you can roughly halve this number. What is the bottom line? If you're not interested in the details, here are the stats of the strategy based on how I traded it.
Extended: 223.46 R of return, 2.34 of profit factor, 0.72 R of expected value, 46.13% winrate. The average win is 2.72 R while the average loss is -1.00 R.
Unextended: 172.20 R of return, 2.19 of profit factor, 0.56 R of expected value, 53.23% winrate. The average win is 1.92 R while the average loss is -1.00 R.
The highest drawdown for both systems was 18 R. This seems like a lot, but remember you're splitting risk in half.
Here you can see the two uncompounded equity curves side by side: red is unextended and blue is extended. Who wins? The test suggests the strategy to be more profitable with the extended target. In addition, most of the trades that reached the unextended target but reversed before reaching the extended, were trades that I would have most likely not have taken with the extented target. This is because there was a resistance/support area in the way of the -100.0 extension level, but there was enough room for price to reach the -61.8 level. I will probably trade this strategy using the -100.0 level as target, unless there is an area in the way. In that case I will go for the unextended target. Drawdown management The expected losing streak for this system, using the extended target, is 7 trades in a row in a sample size of 100 trades. My goal is to have a drawdown cap of 4%, so my risk per trade will be 0.54%. If I ever find myself in a losing streak of more than 8 trades, I will reduce my risk per trade further. What's next? I'll be taking this strategy live. The wisest move would be to repeat the same testing over lower timeframes to verify the edge plays out there as well, but I would not be able to trust my results because I would have vague memories of where price went because of the testing I just did. I also believe markets are fractals, so I see no reason why this wouldn't work on lower timeframes. Before going live, I will expand this spreadsheet to include more specific analysis and I will continue backtesting at a slower pace. The goal is to reach 20 years of backtesting over these 28 pairs and put everything into this spreadsheet. It's not something I will do overnight, but I'll probably do one year every odd day, and maybe a couple more during the weekend. I think I don't have much else to add. I like the strategy. Feel free to ask questions.
I have a habit of backtesting every strategy I find as long as it makes sense. I find it fun, and even if the strategy ends up being underperforming, it gives me a good excuse to gain valuable chart experience that would normally take years to gather. After I backtest something, I compare it to my current methodology, and usually conclude that mine is better either because it has a better performance or the new method requires too much time to manage (Spoiler: until now, I like this better) During the last two days, I have worked on backtesting ParallaxFx strategy, as it seemed promising and it seemed to fit my personality (a lazy fuck who will happily halve his yearly return if it means he can spend 10% less time in front of the screens). My backtesting is preliminary, and I didn't delve very deep in the data gathering. I usually track all sort of stuff, but for this first pass, I sticked to the main indicators of performance over a restricted sample size of markets. Before I share my results with you, I always feel the need to make a preface that I know most people will ignore.
I am words on your screen. You cannot trust me. I could have edited this or literally just typed random numbers on a spreadsheet. Do your own research if you want to trust my conclusion.
Even if you trust me, you need to do backtesting for yourself. The goal of backtesting isn't simply to figure out whether a strategy has an edge: it's a way to get used to how the market flows (valuable experience you will bring on to any other strategy) and how the strategy behaves. You need to see it with your own eyes to allow your subconscious mind to be at ease when it comes time to trade it live: the only way to truly trust your strategy during a period of drawdown, is to have seen it work over hundreds of trades in the past.
Strategy I am not going to go into the strategy in this thread. If you haven't read the series of threads by the guy who shared it, go here. As suggested by my mentioned personality type, I went with the passive management options of ParallaxFx's strategy. After a valid setup forms, I place two orders of half my risk. I add or remove 1 pip from each level to account for spread.
The first at the 23.6 retracement.
The second at the 38.2 retracement.
Both orders have a stop loss at the 78.6 retracement.
Both orders have the same target at the -100.0 extension.
If price moves to the -38.2 extension, I delete any unfilled orders.
I do not scale out, I do not move to breakeven, I place my orders and walk away.
Sample I tested this strategy over the seven major currency pairs: AUDUSD, USDCAD, NZDUSD, GBPUSD, USDJPY, EURUSD, USDCHF. The time period started on January 1th 2018 and ended on July 1th 2020, so a 2.5 years backtest. I tested over the D1 timeframe, and I plan on testing other timeframes. My "protocol" for backtesting is that, if I like what I see during this phase, I will move to the second phase where I'll backtest over 5 years and 28 currency pairs. Units of measure I used R multiples to track my performance. If you don't know what they are, I'm too sleepy to explain right now. This article explains what they are. The gist is that the results you'll see do not take into consideration compounding and they normalize volatility (something pips don't do, and why pips are in my opinion a terrible unit of measure for performance) as well as percentage risk (you can attach variable risk profiles on your R values to optimize position sizing in order to maximize returns and minimize drawdowns, but I won't get into that). Results I am not going to link the spreadsheet directly, because it is in my GDrive folder and that would allow you to see my personal information. I will attach screenshots of both the results and the list of trades. In the latter, I have included the day of entry for each trade, so if you're up to the task, you can cross-reference all the trades I have placed to make sure I am not making things up. Overall results: R Curve and Segmented performance. List of trades: 1, 2, 3, 4, 5, 6, 7. Something to note: I treated every half position as an individual trade for the sake of simplicity. It should not mess with the results, but it simply means you will see huge streaks of wins and losses. This does not matter because I'm half risk in each of them, so a winstreak of 6 trades is just a winstreak of 3 trades. For reference:
Profit Factor: 2.34
Return: 100.47 R
Strike rate: 48.28%
Average win: 2.51 R
Average loss: -1.00 R
Thoughts Nice. I'll keep testing. As of now it is vastly better than my current strategy.
Disclaimer: None of this is financial advice. I have no idea what I'm doing. Please do your own research or you will certainly lose money. I'm not a statistician, data scientist, well-seasoned trader, or anything else that would qualify me to make statements such as the below with any weight behind them. Take them for the incoherent ramblings that they are. TL;DR at the bottom for those not interested in the details. This is a bit of a novel, sorry about that. It was mostly for getting my own thoughts organized, but if even one person reads the whole thing I will feel incredibly accomplished.
For those of you not familiar, please see the various threads on this trading system here. I can't take credit for this system, all glory goes to ParallaxFX! I wanted to see how effective this system was at H1 for a couple of reasons: 1) My current broker is TD Ameritrade - their Forex minimum is a mini lot, and I don't feel comfortable enough yet with the risk to trade mini lots on the higher timeframes(i.e. wider pip swings) that ParallaxFX's system uses, so I wanted to see if I could scale it down. 2) I'm fairly impatient, so I don't like to wait days and days with my capital tied up just to see if a trade is going to win or lose. This does mean it requires more active attention since you are checking for setups once an hour instead of once a day or every 4-6 hours, but the upside is that you trade more often this way so you end up winning or losing faster and moving onto the next trade. Spread does eat more of the trade this way, but I'll cover this in my data below - it ends up not being a problem. I looked at data from 6/11 to 7/3 on all pairs with a reasonable spread(pairs listed at bottom above the TL;DR). So this represents about 3-4 weeks' worth of trading. I used mark(mid) price charts. Spreadsheet link is below for anyone that's interested.
I'm pretty much using ParallaxFX's system textbook, but since there are a few options in his writeups, I'll include all the discretionary points here:
I'm using the stop entry version - so I wait for the price to trade beyond the confirmation candle(in the direction of my trade) before entering. I don't have any data to support this decision, but I've always preferred this method over retracement-limit entries. Maybe I just like the feeling of a higher winrate even though there can be greater R:R using a limit entry. Variety is the spice of life.
I put my stop loss right at the opposite edge of the confirmation candle. NOT at the edge of the 2-candle pattern that makes up the system. I'll get into this more below - not enough trades are saved to justify the wider stops. (Wider stop means less $ per pip won, assuming you still only risk 1%).
All my profit/loss statistics are based on a 1% risk per trade. Because 1 is real easy to multiply.
There are definitely some questionable trades in here, but I tried to make it as mechanical as possible for evaluation purposes. They do fit the definitions of the system, which is why I included them. You could probably improve the winrate by being more discretionary about your trades by looking at support/resistance or other techniques.
I didn't use MBB much for either entering trades, or as support/resistance indicators. Again, trying to be pretty mechanical here just for data collection purposes. Plus, we all make bad trading decisions now and then, so let's call it even.
As stated in the title, this is for H1 only. These results may very well not play out for other time frames - who knows, it may not even work on H1 starting this Monday. Forex is an unpredictable place.
I collected data to show efficacy of taking profit at three different levels: -61.8%, -100% and -161.8% fib levels described in the system using the passive trade management method(set it and forget it). I'll have more below about moving up stops and taking off portions of a position.
And now for the fun. Results!
Total Trades: 241
TP at -61.8%: 177 out of 241: 73.44%
TP at -100%: 156 out of 241: 64.73%
TP at -161.8%: 121 out of 241: 50.20%
Adjusted Proft % (takes spread into account):
TP at -61.8%: 5.22%
TP at -100%: 23.55%
TP at -161.8%: 29.14%
As you can see, a higher target ended up with higher profit despite a much lower winrate. This is partially just how things work out with profit targets in general, but there's an additional point to consider in our case: the spread. Since we are trading on a lower timeframe, there is less overall price movement and thus the spread takes up a much larger percentage of the trade than it would if you were trading H4, Daily or Weekly charts. You can see exactly how much it accounts for each trade in my spreadsheet if you're interested. TDA does not have the best spreads, so you could probably improve these results with another broker. EDIT: I grabbed typical spreads from other brokers, and turns out while TDA is pretty competitive on majors, their minors/crosses are awful! IG beats them by 20-40% and Oanda beats them 30-60%! Using IG spreads for calculations increased profits considerably (another 5% on top) and Oanda spreads increased profits massively (another 15%!). Definitely going to be considering another broker than TDA for this strategy. Plus that'll allow me to trade micro-lots, so I can be more granular(and thus accurate) with my position sizing and compounding.
A Note on Spread
As you can see in the data, there were scenarios where the spread was 80% of the overall size of the trade(the size of the confirmation candle that you draw your fibonacci retracements over), which would obviously cut heavily into your profits. Removing any trades where the spread is more than 50% of the trade width improved profits slightly without removing many trades, but this is almost certainly just coincidence on a small sample size. Going below 40% and even down to 30% starts to cut out a lot of trades for the less-common pairs, but doesn't actually change overall profits at all(~1% either way). However, digging all the way down to 25% starts to really make some movement. Profit at the -161.8% TP level jumps up to 37.94% if you filter out anything with a spread that is more than 25% of the trade width! And this even keeps the sample size fairly large at 187 total trades. You can get your profits all the way up to 48.43% at the -161.8% TP level if you filter all the way down to only trades where spread is less than 15% of the trade width, however your sample size gets much smaller at that point(108 trades) so I'm not sure I would trust that as being accurate in the long term. Overall based on this data, I'm going to only take trades where the spread is less than 25% of the trade width. This may bias my trades more towards the majors, which would mean a lot more correlated trades as well(more on correlation below), but I think it is a reasonable precaution regardless.
Time of Day
Time of day had an interesting effect on trades. In a totally predictable fashion, a vast majority of setups occurred during the London and New York sessions: 5am-12pm Eastern. However, there was one outlier where there were many setups on the 11PM bar - and the winrate was about the same as the big hours in the London session. No idea why this hour in particular - anyone have any insight? That's smack in the middle of the Tokyo/Sydney overlap, not at the open or close of either. On many of the hour slices I have a feeling I'm just dealing with small number statistics here since I didn't have a lot of data when breaking it down by individual hours. But here it is anyway - for all TP levels, these three things showed up(all in Eastern time):
7pm-4am: Fewer setups, but winrate high.
5am-6am: Lots of setups, but but winrate low.
12pm-3pm Medium number of setups, but winrate low.
I don't have any reason to think these timeframes would maintain this behavior over the long term. They're almost certainly meaningless. EDIT: When you de-dup highly correlated trades, the number of trades in these timeframes really drops, so from this data there is no reason to think these timeframes would be any different than any others in terms of winrate. That being said, these time frames work out for me pretty well because I typically sleep 12am-7am Eastern time. So I automatically avoid the 5am-6am timeframe, and I'm awake for the majority of this system's setups.
Moving stops up to breakeven
This section goes against everything I know and have ever heard about trade management. Please someone find something wrong with my data. I'd love for someone to check my formulas, but I realize that's a pretty insane time commitment to ask of a bunch of strangers. Anyways. What I found was that for these trades moving stops up...basically at all...actually reduced the overall profitability. One of the data points I collected while charting was where the price retraced back to after hitting a certain milestone. i.e. once the price hit the -61.8% profit level, how far back did it retrace before hitting the -100% profit level(if at all)? And same goes for the -100% profit level - how far back did it retrace before hitting the -161.8% profit level(if at all)? Well, some complex excel formulas later and here's what the results appear to be. Emphasis on appears because I honestly don't believe it. I must have done something wrong here, but I've gone over it a hundred times and I can't find anything out of place.
Moving SL up to 0% when the price hits -61.8%, TP at -100%
Adjusted Proft % (takes spread into account): 5.36%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%
Adjusted Proft % (takes spread into account): -1.01% (yes, a net loss)
Now, you might think exactly what I did when looking at these numbers: oof, the spread killed us there right? Because even when you move your SL to 0%, you still end up paying the spread, so it's not truly "breakeven". And because we are trading on a lower timeframe, the spread can be pretty hefty right? Well even when I manually modified the data so that the spread wasn't subtracted(i.e. "Breakeven" was truly +/- 0), things don't look a whole lot better, and still way worse than the passive trade management method of leaving your stops in place and letting it run. And that isn't even a realistic scenario because to adjust out the spread you'd have to move your stoploss inside the candle edge by at least the spread amount, meaning it would almost certainly be triggered more often than in the data I collected(which was purely based on the fib levels and mark price). Regardless, here are the numbers for that scenario:
Moving SL up to 0% when the price hits -61.8%, TP at -100%
Winrate(breakeven doesn't count as a win): 46.4%
Adjusted Proft % (takes spread into account): 17.97%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%
Winrate(breakeven doesn't count as a win): 65.97%
Adjusted Proft % (takes spread into account): 11.60%
From a literal standpoint, what I see behind this behavior is that 44 of the 69 breakeven trades(65%!) ended up being profitable to -100% after retracing deeply(but not to the original SL level), which greatly helped offset the purely losing trades better than the partial profit taken at -61.8%. And 36 went all the way back to -161.8% after a deep retracement without hitting the original SL. Anyone have any insight into this? Is this a problem with just not enough data? It seems like enough trades that a pattern should emerge, but again I'm no expert. I also briefly looked at moving stops to other lower levels (78.6%, 61.8%, 50%, 38.2%, 23.6%), but that didn't improve things any. No hard data to share as I only took a quick look - and I still might have done something wrong overall. The data is there to infer other strategies if anyone would like to dig in deep(more explanation on the spreadsheet below). I didn't do other combinations because the formulas got pretty complicated and I had already answered all the questions I was looking to answer.
2-Candle vs Confirmation Candle Stops
Another interesting point is that the original system has the SL level(for stop entries) just at the outer edge of the 2-candle pattern that makes up the system. Out of pure laziness, I set up my stops just based on the confirmation candle. And as it turns out, that is much a much better way to go about it. Of the 60 purely losing trades, only 9 of them(15%) would go on to be winners with stops on the 2-candle formation. Certainly not enough to justify the extra loss and/or reduced profits you are exposing yourself to in every single other trade by setting a wider SL. Oddly, in every single scenario where the wider stop did save the trade, it ended up going all the way to the -161.8% profit level. Still, not nearly worth it.
As I've said many times now, I'm really not qualified to be doing an analysis like this. This section in particular. Looking at shared currency among the pairs traded, 74 of the trades are correlated. Quite a large group, but it makes sense considering the sort of moves we're looking for with this system. This means you are opening yourself up to more risk if you were to trade on every signal since you are technically trading with the same underlying sentiment on each different pair. For example, GBP/USD and AUD/USD moving together almost certainly means it's due to USD moving both pairs, rather than GBP and AUD both moving the same size and direction coincidentally at the same time. So if you were to trade both signals, you would very likely win or lose both trades - meaning you are actually risking double what you'd normally risk(unless you halve both positions which can be a good option, and is discussed in ParallaxFX's posts and in various other places that go over pair correlation. I won't go into detail about those strategies here). Interestingly though, 17 of those apparently correlated trades ended up with different wins/losses. Also, looking only at trades that were correlated, winrate is 83%/70%/55% (for the three TP levels). Does this give some indication that the same signal on multiple pairs means the signal is stronger? That there's some strong underlying sentiment driving it? Or is it just a matter of too small a sample size? The winrate isn't really much higher than the overall winrates, so that makes me doubt it is statistically significant. One more funny tidbit: EUCAD netted the lowest overall winrate: 30% to even the -61.8% TP level on 10 trades. Seems like that is just a coincidence and not enough data, but dang that's a sucky losing streak. EDIT: WOW I spent some time removing correlated trades manually and it changed the results quite a bit. Some thoughts on this below the results. These numbers also include the other "What I will trade" filters. I added a new worksheet to my data to show what I ended up picking.
Total Trades: 75
TP at -61.8%: 84.00%
TP at -100%: 73.33%
TP at -161.8%: 60.00%
Moving SL up to 0% when the price hits -61.8%, TP at -100%: 53.33%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%: 53.33% (yes, oddly the exact same winrate. but different trades/profits)
Adjusted Proft % (takes spread into account):
TP at -61.8%: 18.13%
TP at -100%: 26.20%
TP at -161.8%: 34.01%
Moving SL up to 0% when the price hits -61.8%, TP at -100%: 19.20%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%: 17.29%
To do this, I removed correlated trades - typically by choosing those whose spread had a lower % of the trade width since that's objective and something I can see ahead of time. Obviously I'd like to only keep the winning trades, but I won't know that during the trade. This did reduce the overall sample size down to a level that I wouldn't otherwise consider to be big enough, but since the results are generally consistent with the overall dataset, I'm not going to worry about it too much. I may also use more discretionary methods(support/resistance, quality of indecision/confirmation candles, news/sentiment for the pairs involved, etc) to filter out correlated trades in the future. But as I've said before I'm going for a pretty mechanical system. This brought the 3 TP levels and even the breakeven strategies much closer together in overall profit. It muted the profit from the high R:R strategies and boosted the profit from the low R:R strategies. This tells me pair correlation was skewing my data quite a bit, so I'm glad I dug in a little deeper. Fortunately my original conclusion to use the -161.8 TP level with static stops is still the winner by a good bit, so it doesn't end up changing my actions. There were a few times where MANY (6-8) correlated pairs all came up at the same time, so it'd be a crapshoot to an extent. And the data showed this - often then won/lost together, but sometimes they did not. As an arbitrary rule, the more correlations, the more trades I did end up taking(and thus risking). For example if there were 3-5 correlations, I might take the 2 "best" trades given my criteria above. 5+ setups and I might take the best 3 trades, even if the pairs are somewhat correlated. I have no true data to back this up, but to illustrate using one example: if AUD/JPY, AUD/USD, CAD/JPY, USD/CAD all set up at the same time (as they did, along with a few other pairs on 6/19/20 9:00 AM), can you really say that those are all the same underlying movement? There are correlations between the different correlations, and trying to filter for that seems rough. Although maybe this is a known thing, I'm still pretty green to Forex - someone please enlighten me if so! I might have to look into this more statistically, but it would be pretty complex to analyze quantitatively, so for now I'm going with my gut and just taking a few of the "best" trades out of the handful. Overall, I'm really glad I went further on this. The boosting of the B/E strategies makes me trust my calculations on those more since they aren't so far from the passive management like they were with the raw data, and that really had me wondering what I did wrong.
What I will trade
Putting all this together, I am going to attempt to trade the following(demo for a bit to make sure I have the hang of it, then for keeps):
"System Details" I described above.
TP at -161.8%
Static SL at opposite side of confirmation candle - I won't move stops up to breakeven.
Trade only 7am-11am and 4pm-11pm signals.
Nothing where spread is more than 25% of trade width.
Looking at the data for these rules, test results are:
Adjusted Proft % (takes spread into account): 47.43%
I'll be sure to let everyone know how it goes!
Other Technical Details
ATR is only slightly elevated in this date range from historical levels, so this should fairly closely represent reality even after the COVID volatility leaves the scalpers sad and alone.
The sample size is much too small for anything really meaningful when you slice by hour or pair. I wasn't particularly looking to test a specific pair here - just the system overall as if you were going to trade it on all pairs with a reasonable spread.
Here's the spreadsheet for anyone that'd like it. (EDIT: Updated some of the setups from the last few days that have fully played out now. I also noticed a few typos, but nothing major that would change the overall outcomes. Regardless, I am currently reviewing every trade to ensure they are accurate.UPDATE: Finally all done. Very few corrections, no change to results.) I have some explanatory notes below to help everyone else understand the spiraled labyrinth of a mind that put the spreadsheet together.
I'm on the East Coast in the US, so the timestamps are Eastern time.
Time stamp is from the confirmation candle, not the indecision candle. So 7am would mean the indecision candle was 6:00-6:59 and the confirmation candle is 7:00-7:59 and you'd put in your order at 8:00.
I found a couple AM/PM typos as I was reviewing the data, so let me know if a trade doesn't make sense and I'll correct it.
Insanely detailed spreadsheet notes
For you real nerds out there. Here's an explanation of what each column means:
Pair - duh
Date/Time - Eastern time, confirmation candle as stated above
Win to -61.8%? - whether the trade made it to the -61.8% TP level before it hit the original SL.
Win to -100%? - whether the trade made it to the -100% TP level before it hit the original SL.
Win to -161.8%? - whether the trade made it to the -161.8% TP level before it hit the original SL.
Retracement level between -61.8% and -100% - how deep the price retraced after hitting -61.8%, but before hitting -100%. Be careful to look for the negative signs, it's easy to mix them up. Using the fib% levels defined in ParallaxFX's original thread. A plain hyphen "-" means it did not retrace, but rather went straight through -61.8% to -100%. Positive 100 means it hit the original SL.
Retracement level between -100% and -161.8% - how deep the price retraced after hitting -100%, but before hitting -161.8%. Be careful to look for the negative signs, it's easy to mix them up. Using the fib% levels defined in ParallaxFX's original thread. A plain hyphen "-" means it did not retrace, but rather went straight through -100% to -161.8%. Positive 100 means it hit the original SL.
Trade Width(Pips) - the size of the confirmation candle, and thus the "width" of your trade on which to determine position size, draw fib levels, etc.
Loser saved by 2 candle stop? - for all losing trades, whether or not the 2-candle stop loss would have saved the trade and how far it ended up getting if so. "No" means it didn't save it, N/A means it wasn't a losing trade so it's not relevant.
Spread(ThinkorSwim) - these are typical spreads for these pairs on ToS.
Spread % of Width - How big is the spread compared to the trade width? Not used in any calculations, but interesting nonetheless.
True Risk(Trade Width + Spread) - I set my SL at the opposite side of the confirmation candle knowing that I'm actually exposing myself to slightly more risk because of the spread(stop order = market order when submitted, so you pay the spread). So this tells you how many pips you are actually risking despite the Trade Width. I prefer this over setting the stop inside from the edge of the candle because some pairs have a wide spread that would mess with the system overall. But also many, many of these trades retraced very nearly to the edge of the confirmation candle, before ending up nicely profitable. If you keep your risk per trade at 1%, you're talking a true risk of, at most, 1.25% (in worst-case scenarios with the spread being 25% of the trade width as I am going with above).
Win or Loss in %(1% risk) including spread TP -61.8% - not going to go into huge detail, see the spreadsheet for calculations if you want. But, in a nutshell, if the trade was a win to 61.8%, it returns a positive # based on 61.8% of the trade width, minus the spread. Otherwise, it returns the True Risk as a negative. Both normalized to the 1% risk you started with.
Win or Loss in %(1% risk) including spread TP -100% - same as the last, but 100% of Trade Width.
Win or Loss in %(1% risk) including spread TP -161.8% - same as the last, but 161.8% of Trade Width.
Win or Loss in %(1% risk) including spread TP -100%, and move SL to breakeven at 61.8% - uses the retracement level columns to calculate profit/loss the same as the last few columns, but assuming you moved SL to 0% fib level after price hit -61.8%. Then full TP at 100%.
Win or Loss in %(1% risk) including spread take off half of position at -61.8%, move SL to breakeven, TP 100% - uses the retracement level columns to calculate profit/loss the same as the last few columns, but assuming you took of half the position and moved SL to 0% fib level after price hit -61.8%. Then TP the remaining half at 100%.
Overall Growth(-161.8% TP, 1% Risk) - pretty straightforward. Assuming you risked 1% on each trade, what the overall growth level would be chronologically(spreadsheet is sorted by date).
Based on the reasonable rules I discovered in this backtest:
Date range: 6/11-7/3
Adjusted Proft % (takes spread into account): 47.43%
Demo Trading Results
Since this post, I started demo trading this system assuming a 5k capital base and risking ~1% per trade. I've added the details to my spreadsheet for anyone interested. The results are pretty similar to the backtest when you consider real-life conditions/timing are a bit different. I missed some trades due to life(work, out of the house, etc), so that brought my total # of trades and thus overall profit down, but the winrate is nearly identical. I also closed a few trades early due to various reasons(not liking the price action, seeing support/resistance emerge, etc). A quick note is that TD's paper trade system fills at the mid price for both stop and limit orders, so I had to subtract the spread from the raw trade values to get the true profit/loss amount for each trade. I'm heading out of town next week, then after that it'll be time to take this sucker live!
Date range: 7/9-7/30
Adjusted Proft % (takes spread into account): 20.73%
Starting Balance: $5,000
Ending Balance: $6,036.51
Live Trading Results
I started live-trading this system on 8/10, and almost immediately had a string of losses much longer than either my backtest or demo period. Murphy's law huh? Anyways, that has me spooked so I'm doing a longer backtest before I start risking more real money. It's going to take me a little while due to the volume of trades, but I'll likely make a new post once I feel comfortable with that and start live trading again.
I've recently been working on creating and refining a new edge. Journaling is an essential part of that process and it inspired me to make this post since some people might not see the importance of keeping one.
Journaling is one of the most important aspects of your trading.
It can be a chore, but keeping a trading journal is incredibly useful.
Because if you set one up and use it correctly, that's where you'll find patterns. Patterns in the markets, patterns in your trades, and patterns in your trading behaviour. You can use a journal find new edges. Or to refine your entries, exits, SLs, TPs, holding times, etc. Or to find and address any bad trading behaviours (eg. moving SLs when you shouldn't be, or skipping valid set ups out of fear). You get the idea - it's really handy.
What should you put in your journal?
As much as you can - without discouraging yourself from actually using it consistently. That's going to differ for everyone. Do some googling (or ask people here on reddit) to see what other people have found useful variables to track. There's also lots of templates available online to copy (eg. here or here). Keep in mind that different technical set ups will require different variables to track. A few that I think are very useful yet often overlooked include - maximum adverse excursion, maximum favourable excursion, tracking the performance (using R multiples) of a few alternative exit methods, and the name of the day of the week at entry.
So what should you do?
Step 1 - Think long and hard about the appropriate variables you think you should track - ones that could influence your trade performance. Step 2 - Update your journal regularly. I like to do it at the end of every trading day while the trades are still fresh in my mind. Find what works for you. Step 3 - Periodically go back and analyse your journal. You might find that your win rate drops significantly on Fridays and thus makes your Friday trades have a negative expectancy. You might find that having RSI divergence at your entry signal increases the expectancy of the trade by 13%. You might find that exiting at ATR significantly outperforms both exiting at your Bollinger bands or exiting at a 161.8% fib extension. You get the idea? Step 4 - Act on the information provided by your journal. Skip those Friday trades. Add RSI divergence to your entry requirements. Exit at ATR. Whatever.
Journaling is incredibly useful for backtesting, forward testing, and live trading. Your journal is your best friend. Use one.
Create a folder for trading screenshots. Take a screenshot of the chart every time you enter, exit or modify a trade. Annotate the screenshots in an image editor (eg. MS Paint) if you want. Find a naming convention that works. Here's an example from my folder. Sort this folder in numerical order and you'll have a chronological chart book of all your trades which can be useful for visually searching for patterns.
I use a paid program called Edgewonk as my journal. It's just a glorified excel document that makes the analysis easier. You can just use the filter feature in excel to see how variables (and combinations of variables) affect your trades. Here's an export of some of the things I track in it for one of my set ups.Notethisspreadsheetdoesn'tincludethetrackingofdifferentexitmethods,ortradescreenshots,oranyanalysis.
If you feel like sharing the variables you track in your trading journal, I'm sure people would like to read about them in the comments.
Evaluate yourself, honestly. What kind of attributes will you need reflected in your trading plan? Indecisiveness is not working in your favour when your money is on the line.
While you're trading, your plan should be set solidly - making changes on the fly is a losing proposition. The plan should be re-evaluated when you're out of the market, but not while you're in it! Stick to the plan.
No emotions. Stick to the plan.
Paper trade and backtest your plan before putting your money on the line!
Diversify your portfolio. If you're putting a lot of money on the line, have it spread out over multiple securities in multiple sectors to pad yourself against damaging market movements.
6. A Trading Plan
So you've been following TAWR for the last month - what does your trading plan look like? If you haven't started one yet, that's okay - that's what we start to cover in this week's post. First, you need to do a little soul searching.
Is this the right market for you to trade in?
Unlike other markets, the Bitcoin market does not close, not even on weekends. (International exchanges are for the most part open 6 days out of 7. BTC is around the clock.) This means there is constantly something happening, something to be watching for. Obviously you needn't be watching charts all the time and losing sleep and cuddle time because of a possible overseas news bit making waves - but this does open the market up for a lot of activity and this can be a serious stressor. If this will be too much for you, don't worry! This isn't the only market you can trade in. If this is a serious concern for you, consider other markets on the Forex. There are plenty of currency pairs to trade in that aren't nearly as crazy as those involving XBTs. ...If you're still here and not looking up USD/CHF market behaviour, that must mean you like rollercoasters.
Type of Trader: Being Honest With Yourself
Are you a swing trader? Long-term buy-and-holder looking to make a little extra in the short-term? Just curious what it's like to do what a daytrader does? Answering the question of "what type of trader are you" is important when setting up a trading plan, because certain indicators are better suited to different styles of trading. Your trading style will not necessarily reflect mine. Yours will likely differ a lot from mine and everyone else' - but as long as you can make decisions based off of that plan, and they make you money when followed, it is a good trading plan. Ultimately, the goal of answering that question isn't to give yourself a label, it's to find a set of technical rules that you can follow that 1) make you money, and 2) that you can actually act on. Trader indecisiveness is a serious problem when on the (digital) trading floor. If you have a killer plan that seems like it'll work well for you based on the backtesting, but you find that you can't actually decide when to enter and exit a position because it's reacting very sensitive to market movements, that's trader indecisiveness. Suppose it's not reactive enough and you miss entry points every time they pass? That's also trader indecision. If you can take action based on the indicators, and make money as a result, that's a good plan. If not, go ahead and make revisions to the plan. Identify what's causing your money to disappear into fees and other traders' pockets, and make changes to keep that from happening! I mentioned backtesting. That's important because whenever you come up with (or change) a trading plan, you need to...
PAPER TRADE FIRST.
If you aren't making money on paper, why would you make money in the market? To paper trade, take down your actions based on your prospective trading plan, using actual market data. Follow the market and see if your trades would have made money if you had actually executed them on the market. If you're making satisfying gains consistently on those trades based on the rules of your plan, you can have confidence in your trading plan. If you're losing money or just barely breaking even, consider revisions to your trading plan. You can use historical data to check your plan's profitability, since it's readily available. Bitcoincharts.com and Tradingview.com both let you see historical data from the Bitcoin market, for example. Obviously this will not be terribly useful to you until you've built your plan, but if you've already started to play with some indicators just to get a feel of how they look and react with the data, you'll find those two links somewhat helpful in getting a jump on next week's post.
Stick to the Facts.
Maybe your gut has never done you wrong, but always follow the chart. Befriend the trend. Trust the chart. Facts don't lie. Evidence doesn't lie. Make money by going with the market, not against it, no matter what your emotions or feelings are telling you. This is something I've been guilty of, because the fact is I love Bitcoin. I really do. I love its functionality, its widespread growth, and the fact that it's techy at its decentralized heart. (That's a paradox, by the way.) But when a trader gets too involved with their chosen security, they believe in it for the wrong reasons. As much as I love Bitcoin, I have to sell it if the price goes into a mad nosedive. If you believe in the long-term success of Bitcoin, cool - know why you believe in it. Otherwise, just trade it and don't get too attached to it. One of the key differences between Bitcoin and traditional stocks are that stocks are not food or clothes - you can't eat or wear stocks, so selling them is how you make money (locking in profits vs making gains "on paper"). However, Bitcoin actually does have use. It can be spent like any other currency (except faster!) and therefore having a lot of this security actually does give you a function you might not otherwise have. All the same, decide just how close you want to be to Bitcoin. If you believe it'll always and forever have a value, and will increase in value over time no matter what, then go ahead and collect as many as you can afford. If you have your cautious doubts, be aware of the previous point about getting too close to the security, and trade it like any other stock. It's all about making money, whether you measure your monetary gains in USD or XBTs. This next segment is right out of Barbara Rockefeller's "Technical Analysis for Dummies, 2nd ed." book, and is always true whether you're into cryptocurrencies or traditional stocks.
"Diversification reduces risk. The proof of the concept in financial math won its proponents the Nobel prize, but the old adage has been around for centuries: “Don’t put all your eggs in one basket.” In technical trading, diversification applies in two places:
Your choice of indicators: You improve the probability of a buy/sell signal being correct when you use a second, noncorrelated indicator to confirm it. You don’t get confirmation of a buy/sell signal when you consult a second indicator that works on the same principle as the first indicator. Momentum...doesn’t confirm relative strength because it adds no new information. Widen your horizon beyond a few indicators, and seek different concept indicators instead of torturing old indicators to come up with better parameters.
Your choice of securities: You reduce risk when you trade two securities whose prices move independently from one another. If you trade a technology stock, you achieve no diversification at all by adding another technology stock. Instead, you may get a better balance of risk by adding a stock from a different sector. If you trade metals futures, add something from agriculture or finance to get diversification. You can estimate degree of correlation scientifically with a spreadsheet or informally by eye (charting both securities in the same space)."
Deciding on Indicators
Wait til next week and we'll go over those! We'll see which ones fit with faster or slower trading plans (both are useful in Bitcoin) and you get to branch off from there and build your plan accordingly.
I'll welcome redditors to either comment or PM me their trading plans I'll do my best to look them over and offer suggestions or warnings as I see them. Again, I'm no guru or all-knowing being, and I'm not a certified trader or money manager or anything of that nature - but I'll offer the benefit of my research over the last few months regarding the indicators we've covered. Stay curious, make money, have fun and see you next week.
The Backtesting Expert is a spreadsheet model that allows you to create trading strategies using the technical indicators and running the strategies through historical data. The performance of the strategies can then be measured and analyzed quickly and easily. During the backtesting process, the Backtesting Expert runs through the historical data in a row by row manner from top to bottom ... You can do this using a simple Excel spreadsheet. Examples of information you can note include your entry point, risk/reward ratio, stop-loss, take-profit, and the trade result. Step 5: If you can’t identify a setup, keep moving the chart forward bar by bar. Step 6: Repeat steps 4 and 5. The pros and cons of manually backtesting in MT4. The two biggest benefits of manually backtesting in MT4 ... Backtesting Excel Trading Spreadsheet. Now lets backtest our algorithm on historical data to see how it would have performed in the past. The data we are going to be using is hourly closing prices of SBIN starting from 2009 until 2017. Let us write a macro/subroutine which runs on the data, and writes all the trades and the PnL statements in another sheet. This is how our data looks like . Now ... Conclusion Forex Trading Journal Excel Spreadsheet. These are some ideas; there are dozens of other questions that a journal can help answer. With this, we do not want to tell you to analyze the trades more than necessary because then we fall back to the opposite problem, the so-called analysis paralysis (the psychological block because of excessive analyzes). However, a successful trader is ... Using an excel spreadsheet for backtesting Forex strategies is a common method in this type of backtesting. How to Backtest a Trading Strategy Using Excel. Many traders believe that one shouldn't have to be a programmer or an engineer to backtest a strategy. This method takes us back to the very basics, which anyone can use. Spreadsheet programmes such as Excel are among the best ways to ... Forex Manual Backtest – Backtesting Report and Using Excel. Post Author: david; Post Category: Articles; In this article, we are going to see what information we need to collect for a manual backtest, particularly in forex; how to gather them, what can be found in a backtesting report and what do they tell us and how we can calculate the information we’ve gathered using Excel. If you are ... Forex Excel Spreadsheet For Backtesting Strategies [box type=”bio”] Jayantha has been selected as Campus Ambassador at AlgoJi- 2017. He is pursuing B.Tech. + M.Tech. (Dual Degree) from IIT BHU. His hobbies include maths and music.[/box]Forex Excel Spreadsheet shows you how to code and backtest strategies for the international currencies market. The Foreign Exchange market is the largest ...
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